Akojwar sudhir (9 risultati)

Condizione: New. pp. 104.

paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kshirsagar PravinPravin R. Kshirsagar is currently working as an Assistant Professor at S.B. Jain Institute of Technology, Management and Research, Nagpur, Maharashtra, India.Brain Tumor is one of the most harmful Neurological Di. …

Condizione: New. Print on Demand pp. 104.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: R. Kshirsagar PravinDr. Pravin R. Kshirsagar, Associate Professor, ETC Department,at GHRECM, Pune (M.S),India.Dr. Sudhir G. Akojwar, Associate Professor, Head, Department of Electronics and Telecommunication Engineering, at Governmen.…

Condizione: New. PRINT ON DEMAND pp. 104.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: A. Chavan SalimDr.Salim A. Chavan working as a professor, Principal of Waingainga college of engineering,Nagpur.Dr. Sudhir G. Akojwar working as an Associate professor, Head of ETC Department at Government college of Engineering,Chan. …

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book proposes two novel algorithms for function classification and prediction that extends a three layered Feed Forward Neural Network (FFNN) and the standard Generalized Regression Neural Network (GRNN).In this book genetic algorithm(GA) is used inside the particle swarm optimization(PSO) algorithm to bring the worst particle in PSO search space nearer to the food. This helps in faster convergence of PSO algorithm and the possibility of the algorithm to get stuck at the local minima is eliminated.The detailed analysis of results and comparisons show that the proposed algorithms have effectively improved the performance of a neural network as a classifier and predictor and obtained the better accuracy with minimum mean square error than the non optimized neural networks.…